Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study) : a multicentre, cross-sectional study in England
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
OBJECTIVES: To investigate the usefulness of using automated appointment check-in screens to collect brief research data from patients, prior to their general practice consultation.
DESIGN: A descriptive, cross-sectional study.
SETTING: Nine general practices in the West Midlands, UK. Recruitment commenced in Autumn 2018 and was concluded by 31 March 2019.
PARTICIPANTS: All patients aged 18 years and above, self-completing an automated check-in screen prior to their general practice consultation, were invited to participate during a 3-week recruitment period.
PRIMARY AND SECONDARY OUTCOME MEASURES: The response rate to the use of the automated check-in screen as a research data collection tool was the primary outcome measure. Secondary outcomes included responses to the two research questions and an assessment of impact of check-in completion on general practice operationalisation RESULTS: Over 85% (n=9274) of patients self-completing an automated check-in screen participated in the Automated Check-in Data Collection Study (61.0% (n=5653) women, mean age 55.1 years (range 18-98 years, SD=18.5)). 96.2% (n=8922) of participants answered a 'clinical' research question, reporting the degree of bodily pain experienced during the past 4 weeks: 32.9% (n=2937) experienced no pain, 28.1% (n=2507) very mild or mild pain and 39.0% (n=3478) moderate, severe or very severe pain. 89.3% (n=8285) of participants answered a 'non-clinical' research question on contact regarding future research studies: 46.9% (n=3889) of participants responded 'Yes, I'd be happy for you to contact me about research of relevance to me'.
CONCLUSIONS: Using automated check-in facilities to integrate research into routine general practice is a potentially useful way to collect brief research data from patients. With the COVID-19 pandemic initiating an extensive digital transformation in society, now is an ideal time to build on these opportunities and investigate alternative, innovative ways to collect research data.
TRIAL REGISTRATION NUMBER: ISRCTN82531292.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:13 |
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| Enthalten in: |
BMJ open - 13(2023), 1 vom: 05. Jan., Seite e062389 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lawton, Sarah [VerfasserIn] |
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| Links: |
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| Themen: |
Health informatics |
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| Anmerkungen: |
Date Completed 09.01.2023 Date Revised 31.01.2023 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1136/bmjopen-2022-062389 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a OBJECTIVES: To investigate the usefulness of using automated appointment check-in screens to collect brief research data from patients, prior to their general practice consultation | ||
| 520 | |a DESIGN: A descriptive, cross-sectional study | ||
| 520 | |a SETTING: Nine general practices in the West Midlands, UK. Recruitment commenced in Autumn 2018 and was concluded by 31 March 2019 | ||
| 520 | |a PARTICIPANTS: All patients aged 18 years and above, self-completing an automated check-in screen prior to their general practice consultation, were invited to participate during a 3-week recruitment period | ||
| 520 | |a PRIMARY AND SECONDARY OUTCOME MEASURES: The response rate to the use of the automated check-in screen as a research data collection tool was the primary outcome measure. Secondary outcomes included responses to the two research questions and an assessment of impact of check-in completion on general practice operationalisation RESULTS: Over 85% (n=9274) of patients self-completing an automated check-in screen participated in the Automated Check-in Data Collection Study (61.0% (n=5653) women, mean age 55.1 years (range 18-98 years, SD=18.5)). 96.2% (n=8922) of participants answered a 'clinical' research question, reporting the degree of bodily pain experienced during the past 4 weeks: 32.9% (n=2937) experienced no pain, 28.1% (n=2507) very mild or mild pain and 39.0% (n=3478) moderate, severe or very severe pain. 89.3% (n=8285) of participants answered a 'non-clinical' research question on contact regarding future research studies: 46.9% (n=3889) of participants responded 'Yes, I'd be happy for you to contact me about research of relevance to me' | ||
| 520 | |a CONCLUSIONS: Using automated check-in facilities to integrate research into routine general practice is a potentially useful way to collect brief research data from patients. With the COVID-19 pandemic initiating an extensive digital transformation in society, now is an ideal time to build on these opportunities and investigate alternative, innovative ways to collect research data | ||
| 520 | |a TRIAL REGISTRATION NUMBER: ISRCTN82531292 | ||
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| 650 | 4 | |a PUBLIC HEALTH | |
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| 700 | 1 | |a Muller, Sara |e verfasserin |4 aut | |
| 700 | 1 | |a Wathall, Simon |e verfasserin |4 aut | |
| 700 | 1 | |a Helliwell, Toby |e verfasserin |4 aut | |
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